Higher measured than modeled ozone production at increased NOx levels in the Colorado Front Range

Abstract. Chemical models must correctly calculate the ozone formation rate, P(O3), to accurately predict ozone levels and to test mitigation strategies. However, air quality models can have large uncertainties in P(O3) calculations, which can create uncertainties in ozone forecasts, especially during the summertime when P(O3) is high. One way to test mechanisms is to compare modeled P(O3) to direct measurements. During summer 2014, the Measurement of Ozone Production Sensor (MOPS) directly measured net P(O3) in Golden, CO, approximately 25 km west of Denver along the Colorado Front Range. Net P(O3) was compared to rates calculated by a photochemical box model that was constrained by measurements of other chemical species and that used a lumped chemical mechanism and a more explicit one. Median observed P(O3) was up to a factor of 2 higher than that modeled during early morning hours when nitric oxide (NO) levels were high and was similar to modeled P(O3) for the rest of the day. While all interferences and offsets in this new method are not fully understood, simulations of these possible uncertainties cannot explain the observed P(O3) behavior. Modeled and measured P(O3) and peroxy radical (HO2 and RO2) discrepancies observed here are similar to those presented in prior studies. While a missing atmospheric organic peroxy radical source from volatile organic compounds co-emitted with NO could be one plausible solution to the P(O3) discrepancy, such a source has not been identified and does not fully explain the peroxy radical model–data mismatch. If the MOPS accurately depicts atmospheric P(O3), then these results would imply that P(O3) in Golden, CO, would be NOx-sensitive for more of the day than what is calculated by models, extending the NOx-sensitive P(O3) regime from the afternoon further into the morning. These results could affect ozone reduction strategies for the region surrounding Golden and possibly other areas that do not comply with national ozone regulations. Thus, it is important to continue the development of this direct ozone measurement technique to understand P(O3), especially under high-NOx regimes

Atmospheric Acetaldehyde: Importance of Air-Sea Exchange and a Missing Source in the Remote Troposphere.

We report airborne measurements of acetaldehyde (CH3CHO) during the first and second deployments of the National Aeronautics and Space Administration (NASA) Atmospheric Tomography Mission (ATom). The budget of CH3CHO is examined using the Community Atmospheric Model with chemistry (CAM-chem), with a newly-developed online air-sea exchange module. The upper limit of the global ocean net emission of CH3CHO is estimated to be 34 Tg a-1 (42 Tg a-1 if considering bubble-mediated transfer), and the ocean impacts on tropospheric CH3CHO are mostly confined to the marine boundary layer. Our analysis suggests that there is an unaccounted CH3CHO source in the remote troposphere and that organic aerosols can only provide a fraction of this missing source. We propose that peroxyacetic acid (PAA) is an ideal indicator of the rapid CH3CHO production in the remote troposphere. The higher-than-expected CH3CHO measurements represent a missing sink of hydroxyl radicals (and halogen radical) in current chemistry-climate models

Atmospheric Benzene Observations from an Oil and Gas Field in the Denver Julesburg Basin in July and August 2014

High time resolution measurements of volatile organic compounds (VOCs) were collectedusing a proton-transfer-reaction quadrupole mass spectrometry (PTR-QMS) instrument at the PlattevilleAtmospheric Observatory (PAO) in Colorado to investigate how oil and natural gas (ONG) developmentimpacts air quality within the Wattenburg Gas Field (WGF) in the Denver-Julesburg Basin. The measurementswere carried out in July and August 2014 as part of NASAs Deriving Information on Surface Conditions fromColumn and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign. ThePTR-QMS data were supported by pressurized whole air canister samples and airborne vertical and horizontalsurveys of VOCs. Unexpectedly high benzene mixing ratios were observed at PAO at ground level (meanbenzene 0.53 ppbv, maximum benzene 29.3 ppbv), primarily at night (mean nighttime benzene 0.73ppbv). These high benzene levels were associated with southwesterly winds. The airborne measurementsindicate that benzene originated from within the WGF, and typical source signatures detected in the canistersamples implicate emissions from ONG activities rather than urban vehicular emissions as primary benzenesource. This conclusion is backed by a regional toluene-to-benzene ratio analysis which associated southerlyflow with vehicular emissions from the Denver area. Weak benzene-to-CO correlations confirmed that trafficemissions were not responsible for the observed high benzene levels. Previous measurements at the BoulderAtmospheric Observatory (BAO) and our data obtained at PAO allow us to locate the source of benzeneenhancements between the two atmospheric observatories. Fugitive emissions of benzene from ONGoperations in the Platteville area are discussed as the most likely causes of enhanced benzene levels at PAO

An online air-sea exchange model framework for trace gases powered by machine- learning

The ocean emits a wide range of trace gases, such as volatile organic compounds, or sulfur-,nitrogen-, and halogen-containing compounds. Many of these gases play critical roles in the atmosphere, including aerosol and cloud formation, tropospheric and stratospheric ozone budget, as well as the self-cleaning capacity of the atmosphere. Most chemistry-climate models use prescribed oceanic emissions (often derived from observations). These prescribed (offline) emissions generally do not respond to changes in local conditions. A process-level representation of the bi-directional oceanic emissions of trace gases remains challenging, mainly because the ocean biogeochemicalprocesses controlling the natural synthesis of these compounds in the seawater remain poorly understood. We present a new online air-sea exchange framework for the NCAR CESM2, with an observationally trained machine-learning emulator to couple the ocean biogeochemistry with the air-sea exchange. This machine-learning based approach so far has been tested for a number of important trace gases, including dimethyl sulfide (DMS), acetone, bromoform (CHBr 3 ), and dibromomethane (CH 2 Br 2 ), and the preliminary results are evaluated with observations around the globe. This new model framework is more skillful than the widely used top-down approaches for representing the seasonal/spatial variations and the annual means of atmospheric concentrations. The new approach improves the model predictability for the coupled earth system model, and can be used as a basis for investigating the future ocean emissions and feedbacks under climate change.Fil: Wang, Siyuan. National Center for Atmospheric Research; Estados UnidosFil: Emmons, Louisa K.. National Center for Atmospheric Research; Estados UnidosFil: Tilmes, Simone. National Center for Atmospheric Research; Estados UnidosFil: Kinnison, Douglas E.. National Center for Atmospheric Research; Estados UnidosFil: Long, Mateo C.. National Center for Atmospheric Research; Estados UnidosFil: Lamarque, Jean Francoise. National Center for Atmospheric Research; Estados UnidosFil: Apel, Eric C.. National Oceanic & Atmospheric Administration, Esrl; Estados UnidosFil: Hornbrook, Rebecca S.. Centro Nacional de Investigación Atmosférica; Estados UnidosFil: Montzka, Stephen. National Ocean And Atmospheric Administration; Estados UnidosFil: Saiz López, Alfonso. Consejo Superior de Investigaciones Científicas; EspañaFil: Fernandez, Rafael Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Tecnológica Nacional. Facultad Regional de Mendoza; ArgentinaAmerican Geophysical Union Fall MeetingSan FranciscoEstados UnidosAmerican Geophysical Unio

Heterogeneous N2O5 Uptake During Winter: Aircraft Measurements During the 2015 WINTER Campaign and Critical Evaluation of Current Parameterizations

Nocturnal dinitrogen pentoxide (N2O5) heterogeneous chemistry impacts regional air quality and the distribution and lifetime of tropospheric oxidants. Formed from the oxidation of nitrogen oxides, N2O5 is heterogeneously lost to aerosol with a highly variable reaction probability, γ(N2O5), dependent on aerosol composition and ambient conditions. Reaction products include soluble nitrate (HNO3 or NO3−) and nitryl chloride (ClNO2). We report the first‐ever derivations of γ(N2O5) from ambient wintertime aircraft measurements in the critically important nocturnal residual boundary layer. Box modeling of the 2015 Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign over the eastern United States derived 2,876 individual γ(N2O5) values with a median value of 0.0143 and range of 2 × 10−5 to 0.1751. WINTER γ(N2O5) values exhibited the strongest correlation with aerosol water content, but weak correlations with other variables, such as aerosol nitrate and organics, suggesting a complex, nonlinear dependence on multiple factors, or an additional dependence on a nonobserved factor. This factor may be related to aerosol phase, morphology (i.e., core shell), or mixing state, none of which are commonly measured during aircraft field studies. Despite general agreement with previous laboratory observations, comparison of WINTER data with 14 literature parameterizations (used to predict γ(N2O5) in chemical transport models) confirms that none of the current methods reproduce the full range of γ(N2O5) values. Nine reproduce the WINTER median within a factor of 2. Presented here is the first field‐based, empirical parameterization of γ(N2O5), fit to WINTER data, based on the functional form of previous parameterizations

Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model : TES regressions are generally consistent with the model : aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS > 0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1-2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 1.0, 0.05 and 8.6 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.75 for expanding canopies with leaf area index < 2.0) provide a more realistic simulation of seasonal methanol concentrations in midlatitudes on the basis of IASI, TES, and ground-based measurements

Sources and Secondary Production of Organic Aerosols in the Northeastern United States during WINTER

Most intensive field studies investigating aerosols have been conducted in summer, and thus, wintertime aerosol sources and chemistry are comparatively poorly understood. An aerosol mass spectrometer was flown on the National Science Foundation/National Center for Atmospheric Research C‐130 during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) 2015 campaign in the northeast United States. The fraction of boundary layer submicron aerosol that was organic aerosol (OA) was about a factor of 2 smaller than during a 2011 summertime study in a similar region. However, the OA measured in WINTER was almost as oxidized as OA measured in several other studies in warmer months of the year. Fifty‐eight percent of the OA was oxygenated (secondary), and 42% was primary (POA). Biomass burning OA (likely from residential heating) was ubiquitous and accounted for 33% of the OA mass. Using nonvolatile POA, one of two default secondary OA (SOA) formulations in GEOS‐Chem (v10‐01) shows very large underpredictions of SOA and O/C (5×) and overprediction of POA (2×). We strongly recommend against using that formulation in future studies. Semivolatile POA, an alternative default in GEOS‐Chem, or a simplified parameterization (SIMPLE) were closer to the observations, although still with substantial differences. A case study of urban outflow from metropolitan New York City showed a consistent amount and normalized rate of added OA mass (due to SOA formation) compared to summer studies, although proceeding more slowly due to lower OH concentrations. A box model and SIMPLE perform similarly for WINTER as for Los Angeles, with an underprediction at ages \u3c6 hr, suggesting that fast chemistry might be missing from the models

Observations of APAN during TexAQS 2000

Measurements of peroxycarboxylic nitric anhydrides (PANs) made in Houston, Texas during TexAQS (Texas Air Quality Study) 2000 showed a relatively abundant PAN compound that had not been identified in previous studies in North America [cf. Williams et al., 2000]. This compound was hypothesized to be peroxyacrylic nitric anhydride { CH2=CHC(O)OONO2, APAN} based on the work of Tanimoto and Akimoto, [2001]. APAN was synthesized and characterized on one of the two GC systems used to make those measurements, subsequent to the TexAQS 2000 field study, confirming that APAN was observed during TexAQS 2000, both on the ground and in airborne measurements. Mixing ratios of APAN were estimated from the response of the system to PAN and PPN and ranged up to 502 pptv, which was 30% of PAN. High APAN values were associated with the precursor species 1,3-butadiene and acrolein, which had local petrochemical sources. The presence of APAN at these unprecedented levels demonstrates the impact of these reactive VOC species, and may have associated health effects

Wet scavenging of soluble gases in DC3 deep convective storms using WRF-Chem simulations and aircraft observations

We examine wet scavenging of soluble trace gases in storms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. We conduct high-resolution simulations with the Weather Research and Forecasting model with Chemistry (WRF-Chem) of a severe storm in Oklahoma. The model represents well the storm location, size, and structure as compared with Next Generation Weather Radar reflectivity, and simulated CO transport is consistent with aircraft observations. Scavenging efficiencies (SEs) between inflow and outflow of soluble species are calculated from aircraft measurements and model simulations. Using a simple wet scavenging scheme, we simulate the SE of each soluble species within the error bars of the observations. The simulated SEs of all species except nitric acid (HNO_3) are highly sensitive to the values specified for the fractions retained in ice when cloud water freezes. To reproduce the observations, we must assume zero ice retention for formaldehyde (CH_2O) and hydrogen peroxide (H_2O_2) and complete retention for methyl hydrogen peroxide (CH_3OOH) and sulfur dioxide (SO_2), likely to compensate for the lack of aqueous chemistry in the model. We then compare scavenging efficiencies among storms that formed in Alabama and northeast Colorado and the Oklahoma storm. Significant differences in SEs are seen among storms and species. More scavenging of HNO_3 and less removal of CH_3OOH are seen in storms with higher maximum flash rates, an indication of more graupel mass. Graupel is associated with mixed-phase scavenging and lightning production of nitrogen oxides (NO_x), processes that may explain the observed differences in HNO_3 and CH_3OOH scavenging